Uploaded November 2025 | Updated September 2026, 2 weeks ago
Instrument your TypeScript LLM agents with OpenInference and Arize Phoenix for end-to-end tracing, debugging, and LLM evals. In this walkthrough, we wire up auto-instrumentation for an AI agent, stream spans into an open source observability platform, and layer on goal-completion and tool-correctness evals to turn traces into real observability and quality metrics for your agentic workflows.
🔗 Docs: Mastra tracing with Phoenix — arize.com/docs/phoenix/integrations/frameworks/mastra/mastra-tracing
đź”— Join the Arize AI community & events: arize.com/community
đź”— Follow Sri Chavali: linkedin.com/in/srilakshmi-chavali
#llmagents #opentelemetry #openinference #arize #phoenix #aiobservability
Instrument your TypeScript LLM agents with OpenInference and Arize Phoenix for end-to-end tracing, debugging, and LLM evals. In this walkthrough, we wire up auto-instrumentation for an AI agent, stream spans into an open source observability platform, and layer on goal-completion and tool-correctness evals to turn traces into real observability and quality metrics for your agentic workflows.
🔗 Docs: Mastra tracing with Phoenix — arize.com/docs/phoenix/integrations/frameworks/mastra/mastra-tracing
đź”— Join the Arize AI community & events: arize.com/community
đź”— Follow Sri Chavali: linkedin.com/in/srilakshmi-chavali
#llmagents #opentelemetry #openinference #arize #phoenix #aiobservability
